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Evaluation of angular and positional changes of maxillary third molars following premolar extraction, molar distalization, and non-extraction treatments.
BMC Oral Health
January 2025
Department of Orthodontics, Afyonkarahisar Health Sciences University Faculty of Dentistry, Afyonkarahisar, Turkey.
Background: To compare the effects of first premolar extraction, molar distalization, and non-extraction treatments on the angulation and vertical positions of maxillary second molars (MxM2s) and maxillary third molars (MxM3s). To our knowledge, this is the first study to compare the effects of three different treatment types on MxM3 simultaneously.
Methods: Initial (T0) and final (T1) panoramic radiographs of three different patient groups were analyzed: first premolar extraction group (n = 26 patients, 52 MxM2, 52 MxM3), molar distalization group (n = 20 patients, 40 MxM2, 40 MxM3), and non-extraction group (n = 31 patients, 62 MxM2, 62 MxM3).
Tooth replacement of the filter-feeding pterosaur Forfexopterus and its implications for ecological adaptation.
An Acad Bras Cienc
January 2025
Shandong University of Science and Technology, College of Earth Science and Engineering, 579, Qianwangang Road, Huangdao, Qingdao, Shandong Province, 266590, China.
A "comb-dentition", characterized by long, needle-like, and closely-spaced teeth, is found in the ctenochasmatid pterosaurs as an adaptation for filter-feeding. However, little is known about their tooth replacement pattern, hindering our understanding of the development of the filter-feeding apparatus of the clade. Here, we describe the tooth replacement of the pterosaur Forfexopterus from the Jehol Biota based on high-resolution X-ray Computed Tomography (CT) reconstruction.
View Article and Find Full Text PDFPrediction of gene expression using histone modification patterns extracted by Particle Swarm Optimization.
Bioinformatics
January 2025
Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, 37099, Germany.
Motivation: Histone modifications play an important role in transcription regulation. Although the general importance of some histone modifications for transcription regulation has been previously established, the relevance of others and their interaction is subject to ongoing research. By training Machine Learning models to predict a gene's expression and explaining their decision making process, we can get hints on how histone modifications affect transcription.
View Article and Find Full Text PDFImpacted lower third molar classification and difficulty index assessment: comparisons among dental students, general practitioners and deep learning model assistance.
BMC Oral Health
January 2025
Bangkok Hospital Dental Center Holistic Care and Dental Implant, Bangkok Hospital, Bangkok, 10310, Thailand.
Background: Assessing the difficulty of impacted lower third molar (ILTM) surgical extraction is crucial for predicting postoperative complications and estimating procedure duration. The aim of this study was to evaluate the effectiveness of a convolutional neural network (CNN) in determining the angulation, position, classification and difficulty index (DI) of ILTM. Additionally, we compared these parameters and the time required for interpretation among deep learning (DL) models, sixth-year dental students (DSs), and general dental practitioners (GPs) with and without CNN assistance.
View Article and Find Full Text PDFIdentifying Autism Spectrum Disorder Based on Machine Learning for Multi-site fMRI.
J Neurosci Methods
January 2025
College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China; the Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen, China. Electronic address:
Background: Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by repetitive stereotypical behavior and social impairment. Early diagnosis is essential for developing a treatment plan for autism. Although multi-site data can expand the dataset to facilitate the process of data analysis, data heterogeneity between sites and the large amount of data make data analysis difficult.
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